Nanopore signals of the DNAformer study

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Auteurs principaux: Sabary, Omer, Bar-Lev, Daniella, Orr, Itai, Etzion, Tuvi, Yaakobi, Eitan
Format: Recurso digital
Publié: Zenodo 2025
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author Sabary, Omer
Bar-Lev, Daniella
Orr, Itai
Etzion, Tuvi
Yaakobi, Eitan
author_facet Sabary, Omer
Bar-Lev, Daniella
Orr, Itai
Etzion, Tuvi
Yaakobi, Eitan
contents <p>This repository contains the complete dataset of raw Nanopore signals supporting the publication:</p> <p>Bar-Lev, D., Orr, I., Sabary, O., Etzion T., & Yakkobi, E.   <strong>Scalable and robust DNA-based storage via coding theory and deep learning.</strong> Nat Mach Intell, <strong>7</strong>, 639–649 (2025)<em>. <a href="https://www.nature.com/articles/s42256-025-01003-z">https://www.nature.com/articles/s42256-025-01003-z.</a><br></em></p> <h4><strong>Dataset description</strong></h4> <p>The repository includes the raw Nanopore signals in two formats: <strong>binned</strong> and <strong>original (unordered)</strong>.</p> <p> </p> <p><strong>Binned format: </strong></p> <p>Each text file corresponds to a specific cluster and is named according to the cluster’s 12-base index (see publication for details). The file contains:</p> <ul> <li> <p>All basecalled reads assigned to that cluster</p> </li> <li> <p>Their associated read IDs (unique identifiers of the signals)</p> </li> <li> <p>The corresponding FAST5 file in which each signal can be found</p> </li> </ul> <p><strong>Original (unordered) format: </strong></p> <p>The raw signals from the pilot experiments are provided directly in this repository.<br>The raw Nanopore signals of the <em>test</em> datasets are available separately in the following Zenodo repository:<br><a href="https://zenodo.org/records/13896773">https://zenodo.org/records/13896773</a>.<br><br></p>
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publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Nanopore signals of the DNAformer study
Sabary, Omer
Bar-Lev, Daniella
Orr, Itai
Etzion, Tuvi
Yaakobi, Eitan
<p>This repository contains the complete dataset of raw Nanopore signals supporting the publication:</p> <p>Bar-Lev, D., Orr, I., Sabary, O., Etzion T., & Yakkobi, E.   <strong>Scalable and robust DNA-based storage via coding theory and deep learning.</strong> Nat Mach Intell, <strong>7</strong>, 639–649 (2025)<em>. <a href="https://www.nature.com/articles/s42256-025-01003-z">https://www.nature.com/articles/s42256-025-01003-z.</a><br></em></p> <h4><strong>Dataset description</strong></h4> <p>The repository includes the raw Nanopore signals in two formats: <strong>binned</strong> and <strong>original (unordered)</strong>.</p> <p> </p> <p><strong>Binned format: </strong></p> <p>Each text file corresponds to a specific cluster and is named according to the cluster’s 12-base index (see publication for details). The file contains:</p> <ul> <li> <p>All basecalled reads assigned to that cluster</p> </li> <li> <p>Their associated read IDs (unique identifiers of the signals)</p> </li> <li> <p>The corresponding FAST5 file in which each signal can be found</p> </li> </ul> <p><strong>Original (unordered) format: </strong></p> <p>The raw signals from the pilot experiments are provided directly in this repository.<br>The raw Nanopore signals of the <em>test</em> datasets are available separately in the following Zenodo repository:<br><a href="https://zenodo.org/records/13896773">https://zenodo.org/records/13896773</a>.<br><br></p>
title Nanopore signals of the DNAformer study
url https://doi.org/10.5281/zenodo.17399364